docstr: :param y: the output of the bijection
  :type y: torch.Tensor
  Inverts y => x.
docstr_tok: [":","param","y",":","the","output","of","the","bijection",":","type","y",":","torch.Tensor","Inverts","y","=",">","x","."]
code: def _inverse(self, y):
      """
      :param y: the output of the bijection
      :type y: torch.Tensor
      Inverts y => x.
      """
  
      M = self.weights() if callable(self.weights) else self.weights
      return self._exp(y, -M)
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  from torch.distributions import Transform, constraints
  from pyro.nn import DenseNN
  from ..conditional import ConditionalTransformModule
  from ..torch_transform import TransformModule
  from ..util import copy_docs_from
label_desc: Use image node_id 5 for calling the ConditionedMatrixExponential obj's underlying member method code with example usage: obj._inverse(y) and returns: self